What the data for this category looks like
Business data for mining and mineral processing mainly comes from geological exploration reports, production operation logs, mineral processing process parameter records, safety supervision work orders, and service inquiry archives. Geological exploration reports include fields such as drill hole number, ore grade, and mining depth, with units of meters and grams/ton. Production logs record shifts, equipment runtime, mineral processing recovery rate, and other content. Data update frequencies vary by type: production logs are updated daily, geological reports are updated in stages as exploration progresses, and service inquiry archives are added in real time. Document structures differ significantly: long text reports are mostly structured paragraphs, while work orders and logs use key-value pair formats.
What constraints these characteristics impose on the "model access and configuration" link
The multi-type and long-text characteristics of mining and mineral processing data require adapting model access to parse documents of different formats. Real-time updated service inquiry archives require controlling model call latency within a reasonable range to avoid impacting inquiry response efficiency. Large differences exist in field units and professional terminology across different documents. This requires ensuring the model can accurately identify and associate corresponding parameters, so context length must be limited during configuration to avoid interference from irrelevant information. Additionally, data security requirements in state-owned enterprise and public sector scenarios require prioritizing privately deployed or locally connected model channels, restricting external data flow.
How to set the configuration
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
maxContext | 8000–12000 token | Adapt to the reference needs of long mining and mineral processing documents, accommodate multiple sections of geological reports and production log content |
maxTokens | 4000 token | Control the output length of service inquiry responses, ensure information is concise and covers core demands |
quoteMaxToken | 1500 characters | Match the long fragment characteristics of mining and mineral processing documents, avoid truncation of key parameters |
temperature | 0.3–0.5 | Maintain rigor in professional responses, reduce the probability of fictional professional data |
AIPROXY_API_ENDPOINT | Fill in according to the deployment environment | Adapt to state-owned enterprise private deployment needs, support custom protocols and local model access |
Three common errors
- The model selection dropdown in the interface continues to flicker. The cause is that the
toolChoiceparameter is not fixed, causing the system to repeatedly switch available model matching rules. - The number of knowledge base recall results does not meet expectations. The cause is that
quoteMaxTokenis not configured correctly, resulting in long document fragments being truncated and unable to fully match inquiry keywords. - The protocol type cannot be customized after accessing a local private model. The cause is that the private protocol is not configured via
AIPROXY_API_ENDPOINT, and the platform's default fixed protocol format is used incorrectly.
How to confirm the configuration is complete
- Submit an inquiry that includes mining depth and ore grade, check whether the referenced document fragments in the response contain correct fields and units.
- View the model call log to confirm that the
maxContextparameter does not trigger a context truncation error. - Test access to a local private model, verify that the response content matches the output format of the private model.
- Simulate high-frequency service inquiry requests, check that the system response delay meets business expectations.
The values provided here are common starting points and should be evaluated against the reader's own samples.
Question material comes from public community discussions. Configuration values are common starting points and should be measured against your own samples. Verified on 2026-09-28.